The relationship between obesity and
diabetic nephropathy in China

Authors: Hui-Mei Chen, MD, PhD, Wen-Wen Shen, MD, PhD, Yong-Chun Ge, MD, Yi-De Zhang,
MD, Hong-Lang Xie, MD, PhD, Zhi-Hong Liu, MD

Affiliation: Research Institute of Nephrology, Nanjing University School of Medicine, Nanjing
210002, P. R. China

Corresponding: Hui-Mei Chen, MD. PhD. Email: chenhuimei@nju.edu.cn
Zhi-Hong Liu, M.D. MD Email: zhihong--liu@hotmail.com
Research Institute of Nephrology, Nanjing University School of Medicine, 305 East Zhongshan
Road, Nanjing 210002, P. R. China. Tel: +86-25-80860218; Fax: +86-25-84801992;
1
Abstract
Background: The epidemic of diabetic nephropathy (DN) has been paralleled by rapid increases in
both obesity and diabetes in China. The aim of this study was to investigate the natural history of DN
and the association of obesity and renal function with diabetes.
Methods: In total, 264 patients with renal biopsy-confirmed DN were examined from 2002 to 2008
and followed up to June 2008 in our institute. Among these, 129 patients were classified into a Kidney
Disease
Outcomes
Quality
Initiative
(K/DOQI)
stage
I
subgroup.
Weight
status,
clinico-histopathological features, the development of end-stage renal disease (ESRD) and increased
proteinuria were evaluated at the baseline of biopsy and during the follow up. Lean, overweight and
obese phenotypes were defined as body mass index (BMI) less than 25kg/m2, 25–28 kg/m2, and more
than 28 kg/m2 over, respectively.
Results: In the patients with renal biopsy-confirmed DN, BMI was 25.5±3.39 kg/m2, with 122
(46.2%), 83 (31.4%) and 59 (22.3%) having lean, overweight and obese phenotypes, respectively.
Mean proteinuria was 3.09±2.32 g/24 h, serum creatinine was 2.02±2.02 mg/dL, and creatinine
clearance rate (Ccr) was 96.0±54.0 mL/min/1.73 m2. Compared with obese patients, lean patients had
a lower Ccr, a higher percentage of anemia, more renal lesions and higher risk for ESRD (HR = 1.812,
P = 0.048). The weight in obese patients decreased significantly after 27 months, and lean patients
had a longer duration of diabetes than obese patients. Regarding patients at K/DOQI stage I, patients
with DN showed similar duration of diabetes regardless of weight status. Minimal weight loss was
recorded in obese patients during follow-up, and they exhibited greater glomerular hyperfiltration and
higher risk for increased proteinuria (HR = 2.872, P = 0.014) than lean patients.
Conclusions: In China, obesity is common in DN patients undergoing biopsy. Initial high levels of
2
proteinuria and subsequent weight loss are the major characteristics of the natural course of DN.
Obesity contributed to increased proteinuria at an early stage, while the lean phenotype was associated
with ESRD development, especially at the later stages.
Key words: diabetic nephropathy; ESRD; obesity; proteinuria
3
Background
Obesity has become a serious worldwide problem. More than 300 million adults are classified as
obese and the global number is predicted to reach 700 million by 2015. In the past, obesity was not a
common condition among the population of China; however, this is no longer the case[1]. Obesity and
diabetes have become a growing challenge, and one million new diabetic cases are reported in China
every year. Increasing evidence suggests that obesity is a risk factor for diabetes and chronic kidney
diseases. As a marker of obesity, high body mass index (BMI) has been reported to be related with
diabetic nephropathy (DN) and end-stage renal disease (ESRD) [2]. A high prevalence of DN and
ESRD has recently been demonstrated among Asians. During the past two decades, the prevalence of
DN has dramatically increased in China [3-4], although the obesity profile among DN patients and the
natural history of DN are not available in this region.
Obesity has been shown to aggravate renal injury associated with diabetes, although this effect is
not consistent in previous studies. The evidence indicating a relationship between obesity and ESRD
is paradoxical [5-6]. Tokashiki et al. showed that decreased BMI was the independent risk factor for
chronic kidney disease, and the effect of obesity on renal survival varied with ethnicity [1, 7]. Without
intensive analysis, the possible role of obesity and weight loss on kidney function is still uncertain
among Chinese patients with DN.
The first aim of our study was to explore the natural history of DN in Chinese patients. The
second aim was to examine the impact of obesity on renal function in such a population. We screened
patients presenting with type 2 diabetes, proteinuria, and biopsy-confirmed DN in our institute, and
demonstrated an association of the obesity epidemic, weight loss with DN, and BMI with renal injury
4
at different stages of diabetes. Obesity and overweight were defined according to the criteria outlined
by the Working Group on Obesity of China [8]. The renal stages were evaluated by K/DOQI (Kidney
Disease Outcomes Quality Initiative) guidelines.
5
Methods
Study population
Information on 15,141 cases was retrieved from patients, who underwent renal biopsy at a single
unit during the period from July 2002 to June 2008 (Research Institute of Nephrology, Nanjing
University School of Medicine, PR China). In this institute, the indications for renal biopsy included
proteinuria and/or hematuria and/or renal insufficiency, with or without coexisting systemic disease
[9]. The biopsies were performed by a group of clinicians, and renal biopsy specimens were examined
by experienced nephrologists using techniques including light microscopy, immunohistology, and
electron microscopy. Final diagnosis was made on the basis of clinical and histological features.
Approval was obtained from the local authorities of Nanjing University, and informed signed consent
was obtained from each patient.
Initially, 757 patients with renal biopsy-confirmed DN were included, according to the following
criteria: 1) type 2 diabetes mellitus (Standards of Medical Care in Diabetes, 2008, ADA [10]); 2)
urinary protein excretion >400mg/24 h; and 3) typical DN lesions in the glomeruli, tubulo-interstitium
or blood vessels [11]. Patients with concomitant conditions such as IgA nephropathy and secondary
renal damage due to hypertension were excluded [12-13]. All patients were recommended to
follow-up in the out-patient center every 3 months; however, information was obtained for only 264
subjects to June 2008. The base characteristics of these 264 subjects were similar to those of the 757
subjects that were initially included (Supplemental Table 1).
Definitions
BMI was calculated as weight (kg) divided by height2 (m2). Based on the cut-off points in
6
Chinese adults [8], BMI was classified as follows: obese, ≥28.0 kg/m2; overweight, 25.0-27.9 kg/m2;
lean <25.0 kg/m2. The proteinuria per 24 hours and creatinine clearance rate (Ccr) were evaluated by
24-hour urine collection at the time of biopsy, and Ccr were calculated with the standard formula:
urine creatinine (mg/dL) × urine volume (mL/min) / serum creatinine (mg/dL) and adjusted for body
surface [14]. Other definitions were used: 1) nephrotic range proteinuria, 24-hour urine protein
excretion ≥3.5 g; 2) hypoalbuminemia, serum albumin levels ≤3.5 g/L; 3) K/DOQ1 stage I, Ccr >90
mL/min/1.73m2 ; and 3) renal insufficiency, Ccr <60 mL/min/1.73m2. Insulin resistance was assessed
using the Homeostasis Model Assessment of Insulin Resistance formula: fasting serum insulin
(μU/mL) × fasting plasma glucose (mmol/L) / 22.5 [15]. Anemia was defined as hemoglobin < 12 and
< 11 g/dL in men and women, respectively.
Periodic acid-Schiff-stained paraffin-embedded sections at ×400 magnification were used to
estimate pathologic lesions [16-17]. The percentages of globally sclerotic glomeruli and
Kimmelstiel-Wilson (K-W) nodules were recorded from 50 glomerular sections for each patient. A
semi-quantitative assessment of renal damage was performed according to mesangial proliferation,
interstitial fibrosis, tubular atrophy and arteriolar hyalinosis [18].
The progression of renal injury was predicted by the development of ESRD and increased
proteinuria. The primary endpoint, ESRD, was defined as the requirement for permanent renal
replacement therapy or serum creatinine exceeding 6.0 mg/dL for more than 1 month without other
causes of renal dysfunction. The secondary endpoint, increased proteinuria, was defined as a 50%
increase from the baseline level of proteinuria.
7
Statistical analysis
Statistical analysis was performed using SPSS, version 11.0 (SPSS Inc, Chicago, IL).
Quantitative variables were expressed as mean ± SD and compared by one-way ANOVA, followed
with Least-Significant Difference (LSD) tests between each pair of groups. In the absence of a normal
distribution, log-transformed data values were used for analysis and the Mann-Whitney test U-test
was used when necessary. Qualitative variables were described as sample size (number of cases) and
percentage (%), which were analyzed by chi-square test or Fisher’s exact test. Cumulative incidence
of ESRD or disease progression was calculated using Kaplan-Meier survival probabilities (1- survival
probabilities). Adjusted relative risks of mortality were calculated using Cox regression analysis.
Two-tailed P-values less than 0.05 were considered statistically significant.
8
Results
Obesity profile of DN patients in China
All 264 patients were diagnosed with type 2 diabetes and renal biopsy-confirmed DN. Analysis
of the baseline characteristics are shown in Figure 1 and Table 1. The mean age of patients with DN
was 53.1 ± 9.06 years (range 31–80). Of the DN patients, 58.3% were male. The average BMI was
25.5 ± 3.39 kg/m2 (range 18.9–36.6), and the frequency of BMI peaked at 24 kg/m2 (Figure 1A).
Among these patients, 22.3% were obese, while 53.8% were obese/overweight. The average
proteinuria was 3.09 ± 2.32 g/24 h (range 0.4–22.9), (Figure 1B), and 37.4% had nephrotic range
proteinuria. Mean serum albumin was 34.5 ± 7.4 g/L, and 53.5% had hypoalbuminemia. Renal Ccr
greatly varied in patients and the frequency of Ccr peaked around 50 mL/s/1.73m2 (Figure 1C). Renal
insufficiency occurred in 32.3% of subjects, 129 (48.9%) patients remained classified as early stage
(K/DOQI stage I), and no patients suffered from ESRD. The mean serum creatinine was 2.02 ± 2.02
mg/dL.
Patients were divided into three groups on the basis of BMI as follows: obese, ≥28.0 kg/m2 (n =
59); overweight, 25–30 kg/m2 (n = 83); and lean, 18–25 kg/m2 (n = 122). The mean age and sex ratio
among the three groups were similar, as were fasting glucose, HbA1c, mean blood pressure and
previous therapy. At the time of diagnosis, the known duration of diabetes among patients ranged
from a few months to 28 years. Compared with the obese patients, the lean patients suffered a longer
duration of diabetes (P < 0.01), although the average history of proteinuria was similar among the
three groups.
Among the lean patients, the percentage of renal insufficiency was 42.6%, presenting Ccr less
9
than 60 mL/s/1.73m2, which was significantly higher than that in the obese or overweight patients (P
< 0.001, ANOVA). When compared with obese patients, the lean patients with DN showed higher
levels of serum creatinine (P = 0.010), a higher percentage of hypoalbuminemia (P = 0.007) and
anemia (P < 0.001), and greater mesangial expansion (P < 0.001), tubular atrophy (P = 0.012) and
incidence of K-W nodules (P < 0.001). Obese patients had larger glomeruli than those with a lean
phenotype (P = 0.031).
Obesity and improved renal survival in DN patients
The information for follow-up was available for only 264 patients, and the median follow-up time was
39.0 months (range 0–87.0) (Figure 2). The median time of follow-up was 39.0, 36.0 and 36.0 months
for the lean, overweight and obese groups, respectively. The levels of fasting glucose fluctuated but
were similar among the three groups (Figure 2B). By the end of the study period, 74 cases (28.8%)
had developed ESRD.
Compared with obese patients, the lean patients had a greater risk for developing ESRD (Figure
2). After 36 months of follow-up, the mean increment of serum creatinine was 126% in the lean group,
while this was 52.7% and 33.5% in the overweight and obese groups, respectively (P < 0.001,
ANOVA). By the end of the study period, 48 (39.4%) lean patients developed ESRD, and the relative
risk of developing ESRD for the lean phenotype was 1.812 (95% CI 1.004–3.268; P = 0.048, Figure
2C). On the other hand, the mean BMI decreased among patients in the overweight or obese groups
(Figure 2D), while no obvious change in BMI was detected in the lean group (data not shown).
Regarding the obese patients, the reduction in BMI reached 1.30 kg/m2 and 2.28 kg/m2 after 36 and 63
months follow-up, respectively. The percentage of obesity in DN patients decreased from 22.3% at
10
baseline to 19.3% at the end of the study period, while the rate of the lean phenotype increased from
46.2% to 58.3%.
Obesity and increased proteinuria at early stage DN
Using the classification of chronic kidney disease, 129 subjects were classified as K/DOQI stage I and
analyzed for an association between obesity and increased proteinuria at the early stage (Table 2). The
demographic profile, including age and sex ratio, was similar between the total patient population
studies and those at the early stage (data not shown). The patients at the early stage were further
divided into three subgroups based on BMI: obese (n = 32), overweight (n = 51) and lean (n = 46).
Among the patients at the early stage, the known duration of diabetes was similar among the
three subgroups, although this factor differed in the total patient population studied and those with DN.
The known duration of proteinuria was similar among the three groups at the early stage, as were the
levels of fasting glucose, HbA1c and mean blood pressure. At the early stage, greater renal damage
was observed in obese patients compared with lean patients, with greater glomerular hyperfiltration
and a lower percentage of anemia (P = 0.027 and P = 0.007, respectively).
Among the patients at the early stage, the median time of follow-up was 30.0 months (Figure 3).
The fasting glucose levels were almost stable during follow-up (Figure 3B). By the end of the study
period, only 2 (1.55%) cases developed ESRD, while 30 (24.8%) patients had increased proteinuria.
The mean levels of proteinuria increased in the obese patients, reaching 11.3% and 63.3% after 36 and
63 months, respectively (Figure 3A). However, no obvious increase in proteinuria was detected in the
lean and overweight subgroups. The relative risk for increased proteinuria was high in the obese
patients, and 12 (37.5%) exhibited a 50% increase in proteinuria compared with the baseline levels.
11
Using the lean group as a reference, obesity showed a significantly higher risk for increased
proteinuria (Hazard ratio 2.872 [95% CI 1.239–6.659], P = 0.014). Compared with the total
population of obese patients studied, the decrease in mean BMI was relatively small in obese patients
at the early stage (P = 0.018) and was only 1.12 kg/m2 after 63 months of follow-up (Figure 3D). The
overweight patients at the early stage did not show obvious changes in BMI.
12
Discussion
With rapid nutrition and lifestyle transitions over the past two decades, the global rate of obesity has
been increasing at an alarming rate, including in China [19]. The frequency of diabetes has risen in
tandem, as obesity is a component of risk factors for diabetes [20]. Today, China has the largest
number of patients with obesity and diabetes mellitus in the world. Furthermore, increasing numbers
of studies have investigated the relationship between obesity and DN in this ethnic group. This study
shows for the first time that obesity and weight loss are common in Chinese patients with
biopsy-confirmed DN.
Although all the patients were from a single unit, the profile of patients is representative of the
characteristics of Chinese patients with renal disease, especially those in Eastern China. In our
institute, there was an abrupt rise in the number of patients undergoing biopsy after 1985, reaching
500 cases per year in 1991, with a further increase to over 1,000 cases per year after 1998 [9].
Recently, the number of renal biopsies performed each year has exceeded 2,000. The expanded pool
of renal biopsies from kidney disease patients makes the epidemiologic investigation more reliable.
However, the patients were not regularly interviewed in our institute because of concerns of economy
and/or distance. The follow-up information, therefore, was relatively limited. Among all 757 patients
with DN, follow-up information was available for only 264 subjects. The baseline characteristics were
similar between the 757 patients and 264 patients (data not shown).
In Chinese patients with biopsy-confirmed DN, 22.3% presented with obesity and 53.7% with
overweight/obesity. The prevalence of obesity was as high as 24.8% in patients with early stage DN.
Compared with the prevalence in the general Chinese population [21], obesity was more common in
13
the patients with DN. High prevalence of obesity has been confirmed in other ethnic groups [22]. The
obese patients with DN in this study exhibited weight loss with diabetes during follow-up. On average,
BMI decreased by 4.62% (2.28 kg/m2) after 63-months in obese patients, while only moderate
decreases were observed in patients at the early stage. This suggested that weight loss was a predictive
marker of poor or declining health for diabetic patients, which was consistent with the findings of
other studies [23]. Accordingly, the patients with lean phenotype had a longer duration of diabetes
than those with obesity. Compared with obese patients, lean patients exhibited more severe renal
injury, including higher percentage of renal insufficiency and a higher score for tubular lesions.
Taking the lean group as the reference, obesity and overweight significantly decreased the risk for
ESRD. This confirmed that a proportion of lean patients suffer from both DN development and
weight loss before renal biopsy, and indicates that weight loss is the major characteristics of the natural
course of DN and shows a predictive effect on DN in China. Thus, the lean phenotype indicates disease
progression. However, a protective role for obesity in renal disease progression was not identified in
this retrospective study.
On the other hand, weight control was generally thought to decrease the risk for renal injury
associated with obesity and diabetes. Our previous study also proved that weight loss decreased
urinary protein by 51% after 24 months in subjects with obesity-related glomerulopathy (ORG) [24].
Saiki et al. reported the protective effect of weight loss using a formula diet on renal function in obese
patients with DN [25]. These results contrast with our findings. In fact, more studies have suggested
the “obesity paradox” in diabetes and renal diseases [26]. In the present study, a lean phenotype and
weight loss were associated with a “deterioration phenomenon” and progression of renal injury in DN
patients in China. On the other hand, obesity contributed to increased proteinuria at the early stage of
14
DN. Among patients at CKD stage I, obese patients showed greater hyperfiltration than lean patients.
Obesity further increased the risk for increased proteinuria by 2.872 compared with the lean patients.
Similar results were found in the subjects with normal renal function or at the early stage of disease.
Thus, the present study using one population of DN patients showed a varied effect of obesity and
weight loss on the progression of DN.
Much evidence has shown that the different effect of weight loss resulted from two different
mechanisms of weight loss: intentional and unintentional. In brief, diet control and extra exercise
leads to intentional weight loss, mainly from the fat mass, thus improving insulin resistance,
inflammation, and subsequent renal injury. However, with the progression of diabetes, high sugar
levels lead to dehydration, muscle breakdown and an unintentional weight loss, which predicted
clinical deterioration. Zoccali [27] suggested that maintenance of the current weight was the best way
to protect against DN. Unfortunately, BMI was the only marker used to evaluate obesity in the present
study, and it was difficult to classify the source of weight loss. As a retrospective study, the different
effect of weight loss on DN was suggested by the “obesity paradox” with no direct evidence in
support of this phenomenon. Further studies, especially prospective cohort studies, are required to
compare the effect of intentional and unintentional weight loss on DN, which might help to explain
the “obesity paradox” and “weight loss paradox” in China.
It should be pointed out that there are several additional limitations associated with this
retrospective study. Serum creatinine levels were used in the present study to define ESRD, although
this is not a sufficient measure of the loss of renal function, as it can be influenced by muscle mass,
nutritional status and gender. In our institute, patients are usually diagnosed with ESRD, when serum
creatinine levels exceed 6 mg/dL for more than 1 month, and other causes of renal disease are
15
excluded. The value of “6 mg/dL” was adopted as a “cut-off” based on the value commonly used in
Chinese medical schools [28]. Although insufficient, serum creatinine is a conveniently tested
measure in clinical practice, and was therefore used as a marker of the loss of renal function.
Because of the limitations of this study in terms of population number and follow-up
information, the development of ESRD developing does not reflect the progression of renal injury in
all patients with DN. According to the different features of DN at different stages, two end-points
were used to assess the progression of DN in the present study. The development of ESRD was used
as the first endpoint, and increased proteinuria was used as the second endpoint only for those patients
at the early stage. It is well known that early stage patients exhibit micro-albuminuria or moderate
proteinuria, with normal levels of serum creatinine [10]. The levels of albuminuria/proteinuria were
shown to be associated with the severity and out-come of renal injury. At a later stage, most patients
had gross proteinuria and increased serum creatinine. High levels of serum creatinine are linked with
ESRD, while the levels of proteinuria fluctuate with diet and other factors. Using diverse end-points,
our study shows that obesity is significantly associated with increased proteinuria in early stage
patients, and the lean phenotype is linked with ESRD in all DN patients.
It should also be noted that a direct effect of obesity has been shown on renal function
contributing to proteinuria and renal lesions [29]. Some obese patients probably suffered from ORG
prior to the diagnosis of type 2 diabetes or DN. It is difficult to distinguish between these two diseases
based on natural history, or from histological features. ORG is characterized by glomerulomegaly and
focal segmental glomerulosclerosis, which can also be observed in DN. Patients with DN, especially
obese subjects, might present with ORG simultaneously. Previous ORG and/simultaneous ORG partly
added to the difference in progression of CKD between lean and overweight/obese patients.
16
Conclusions
Overall, our study demonstrates that obesity is very common among DN patients undergoing renal
biopsy in China, which is associated with the most rapid increases in both obesity and diabetes globally.
Obese patients showed a natural course of DN – heavy proteinuria initially, followed by weight loss.
Obesity seemed to be associated with increased proteinuria at the early stage, while it was associated
with a benefit in terms of improved renal survival at the later stages. Weight loss was accompanied by
the progression of diabetic nephropathy with a prolonged diabetic duration. Lean patients exhibited a
greater acceleration of disease toward ESRD than obese patients. The present study further elucidates
the mechanism of progression of DN in China in relation to obesity and warns of the concurrence of
weight loss and the development of diabetes. Regular evaluation of weight is important for the
patients with DN, as well monitoring of glucose levels, proteinuria and serum creatinine.
Author’s contribution
CHM and LZH designed the study. SWW, GYC and ZYD collected samples and clinical information.
XHL performed the laboratory assays. CHM performed the statistical analyses and wrote the
manuscript. The final version of the manuscript was approved by all authors.
Acknowledgment
This work was partly supported by the National Natural Science Foundation of China (grant
number: 81070579). The funders had no role in study design, data collection and analysis, decision
to publish, or preparation of the manuscript. No additional external funding received for this study.
Declaration of Competing Interests: Nothing to declare.
17
REFERENCES
1.
Ji CY, Cheng TO: Epidemic increase in overweight and obesity in Chinese children from 1985
to 2005. Int J Cardiol 2009, 132(1):1-10.
2.
Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS: Body mass index and risk for end-stage
renal disease. Ann Intern Med 2006, 144(1):21-28.
3.
Hsieh MC, Hsieh YT, Cho TJ, Chen JF, Lin SD, Chen HC, Tu ST: Remission of diabetic
nephropathy in type 2 diabetic Asian population: role of tight glucose and blood pressure
control. Eur J Clin Invest 2011, 41(8):870-878.
4.
Luk A, Chan JC: Diabetic nephropathy--what are the unmet needs? Diabetes Res Clin Pract
2008, 82 Suppl 1:S15-20.
5.
Speakman JR, Westerterp KR: Reverse epidemiology, obesity and mortality in chronic kidney
disease: modelling mortality expectations using energetics. Blood Purif 2010, 29(2):150-157.
6.
Valocikova I, Valocik G, Kristofova B, Druzbacka L: Obesity paradox and chronic kidney
disease. Bratisl Lek Listy 2011, 112(7):402-406.
7.
Pei YP, Greenwood CM, Chery AL, Wu GG: Racial differences in survival of patients on dialysis.
Kidney Int 2000, 58(3):1293-1299.
8.
Zhou BF: Predictive values of body mass index and waist circumference for risk factors of
certain related diseases in Chinese adults--study on optimal cut-off points of body mass index
and waist circumference in Chinese adults. Biomed Environ Sci 2002, 15(1):83-96.
9.
Li LS, Liu ZH: Epidemiologic data of renal diseases from a single unit in China: analysis based
on 13,519 renal biopsies. Kidney Int 2004, 66(3):920-923.
10.
Alberti KG, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its
complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a
WHO consultation. Diabet Med 1998, 15(7):539-553.
11.
J.C. Jennette JLO, M.M. Schwartz, F.G. Silva,: Heptinstall's Pathology of the Kidney, fifth ed.;
1998.
12.
Huang F, Yang Q, Chen L, Tang S, Liu W, Yu X: Renal pathological change in patients with type
2 diabetes is not always diabetic nephropathy: a report of 52 cases. Clin Nephrol 2007,
67(5):293-297.
13.
Tone A, Shikata K, Matsuda M, Usui H, Okada S, Ogawa D, Wada J, Makino H: Clinical features
of non-diabetic renal diseases in patients with type 2 diabetes. Diabetes Res Clin Pract 2005,
69(3):237-242.
14.
Lemann J, Bidani AK, Bain RP, Lewis EJ, Rohde RD: Use of the serum creatinine to estimate
glomerular filtration rate in health and early diabetic nephropathy. Collaborative Study
Group of Angiotensin Converting Enzyme Inhibition in Diabetic Nephropathy. Am J Kidney
Dis 1990, 16(3):236-243.
15.
Chen HM, Chen Y, Zhang YD, Zhang PP, Chen HP, Wang QW, Li LS, Liu ZH: Evaluation of
Metabolic Risk Marker in Obesity-related Glomerulopathy. J Ren Nutr 2011, 21(4):309-315.
16.
Lane PH, Steffes MW, Mauer SM: Estimation of glomerular volume: a comparison of four
methods. Kidney Int 1992, 41(4):1085-1089.
17.
Chen HM, Liu ZH, Zeng CH, Li SJ, Wang QW, Li LS: Podocyte lesions in patients with
obesity-related glomerulopathy. Am J Kidney Dis 2006, 48(5):772-779.
18.
Gellman DD, Pirani CL, Soothill JF, Muehrcke RC, Kark RM: Diabetic nephropathy: a clinical
18
and pathologic study based on renal biopsies. Medicine (Baltimore) 1959, 38:321-367.
19.
Weight loss helps type 2 diabetes patients. Dis Manag Advis 2008, 14(10):11-12.
20.
Ramachandran A, Ma RC, Snehalatha C: Diabetes in Asia. Lancet 2010, 375(9712):408-418.
21.
Wu Y: Overweight and obesity in China. Bmj 2006, 333(7564):362-363.
22.
Maric C, Hall JE: Obesity, metabolic syndrome and diabetic nephropathy. Contrib Nephrol 2011,
170:28-35.
23.
Meltzer AA, Everhart JE: Unintentional weight loss in the United States. Am J Epidemiol 1995,
142(10):1039-1046.
24.
Shen WW, Chen HM, Chen H, Xu F, Li LS, Liu ZH: Obesity-related glomerulopathy: body mass
index and proteinuria. Clin J Am Soc Nephrol 2010, 5(8):1401-1409.
25.
Saiki A, Nagayama D, Ohhira M, Endoh K, Ohtsuka M, Koide N, Oyama T, Miyashita Y, Shirai K:
Effect of weight loss using formula diet on renal function in obese patients with diabetic
nephropathy. Int J Obes (Lond) 2005, 29(9):1115-1120.
26.
Andreotti F, Rio T, Lavorgna A: Body fat and cardiovascular risk: understanding the obesity
paradox. Eur Heart J 2009, 30(7):752-754.
27.
Zoccali C: The obesity epidemics in ESRD: from wasting to waist? Nephrol Dial Transplant
2009, 24(2):376-380.
28.
Wang Y: Medicine: People's Medical Publish Houst, co.; 2010.
29.
Chen HM, Li SJ, Chen HP, Wang QW, Li LS, Liu ZH: Obesity-related glomerulopathy in China:
a case series of 90 patients. Am J Kidney Dis 2008, 52(1):58-65.
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Figure Legends
Figure 1. Histogram of weight mass index (A), proteinuria (B) and creatinine clearance rate (C)
distribution among study subjects with diabetic nephropathy.
Figure 2. The follow-up of glucose control and renal lesions in patients with DN (n=264): A, mean
change in Scr (%); B, mean change in fasting glucose; C, cumulative incidence (%) of end-stage renal
disease: patients with obesity have improved renal survival compared those with lean BMI
(Kaplan–Meier analysis, log-rank, P=0.0231); D, mean change in BMI (%).
Figure 3. The follow-up of glucose control and renal lesions in subjects at K/DOQI stage I (n=129). A,
mean change in proteinuria (%); B, mean change in fasting glucose; C, cumulative incidence (%) of
proteinuria progression: patients with obesity have higher risk of progress of proteinuria compared
those with lean BMI (Kaplan–Meier analysis, log-rank, P=0.0142); D, mean change in BMI (%).
20
TABLES
Table 1. Epidemiological characteristics of subjects with diabetic nephropathy.
Total
Lean Group
BMI < 25
Overweight Group
25 ≤ BMI < 28
Obese Group
BMI ≥ 28
264
122
83
59
BMI (kg/m2)
25.5±3.39
22.6 ± 1.59
26.4 ± 0.85
31.3± 1.91
-
Age (years)
53.1 ± 9.06
54.1 ± 9.34
54.0 ± 8.97
53.1 ± 8.62
0.787
47（56.6%）
34（57.6%）
0.894
No. of patients
Male sex (%)
Known duration of diabetes
(months)
Known duration of proteinuria
(months)
154（58.3%） 73（59.8%）
P value
111 ± 73.7
123 ± 74.8
110 ± 74.9
84.0 ± 62.1**‡
0.002
27.7 ± 41.7
23.7 ± 29.7
28.0 ± 39.7
27.8 ± 56.8
0.698
124 ± 44
125 ± 48
117 ± 34
128 ± 51
0.338
HbA1c (%)
6.66 ± 1.33
6.81 ± 1.50
6.48 ± 1.20
6.61 ± 1.11
0.230
Mean blood pressure (mmHg)
108 ± 14.2
109 ± 14.5
105 ± 13.3
109 ± 14.8
0.139
Proteinuria (g/24h)
3.09 ± 2.32
3.19 ± 2.19
2.97 ± 2.46
3.08 ± 2.69
0.821
3.5g/24h (%)
103 (37.4%)
48 (39.3%)
32 (38.6%)
23 (39.0%)
0.927
3.45 ± 0.74
3.36 ± 0.69
3.46 ± 0.80
3.66 ± 0.74*
0.017
141 (53.5%)
78 (63.9%)
37 (44.6%)**
26 (44.1%)**
0.007
Serum creatinine (mg/dL)
2.02 ±2.02
2.39 ± 2.27
1.52 ± 1.14**
2.00 ± 2.36
0.010
Ccr (mL/min/1.73m2)
97.8 ± 53.4
81.6 ± 51.0
114 ± 57.6**
109 ± 64.8**
< 0.001
85 (32.2%)
52 (42.6%)
18 (21.7%)**
15 (25.4%)**
< 0.001
Uric acid (μmol/L)
400 ± 108
391 ± 110
401 ± 101
418 ± 113
0.340
Hemoglobin (g/dL)
11.2 ± 2.6
10.4 ± 2.3
11.7 ± 2.5**
12.3 ± 2.7**
<0.001
140 (54.9%)
84 (68.9%)
39 (47.0%) **
17 (34.7%) **
< 0.001
Volume of glomerulus (×106 μm3) 4.97 ± 0.71
4.59 ± 0.64
5.13 ± 0.81
5.53 ± 0.68*
0.031
Mean global sclerosis (%)
27.5 ± 24.2
29.1 ± 25.9
26.8 ± 23.4
25.1 ± 21.7
0.634
Mesangial expansion (0-3)
2.51 ± 1.22
2.86 ± 1.14
2.33 ± 1.25*
2.06 ± 1.21**
0.001
K-W nodule (%)
145 (55.4%)
81 (66.4%)
40 (48.2%)*
24 (40.7%)**
<0.001
Interstitial fibrosis (0-3)
1.48 ± 0.72
1.57±0.68
1.35±0.72
1.48±0.87
0.197
Tubular atrophy (0-3)
1.07 ± 0.21
1.14±0.39
1.04 ± 0.37
0.97±0.18*
0.012
Fasting glucose (mg/ dL)
Serum albumin (g/dL)
<3.5 g/dL (%)
< 60 mL/min/1.73m2 (%)
Anemia (%)
NOTE. Values were expressed as expressed as mean ± SD and categorical data expressed as number (%).Abbreviation:
BMI, body mass index; K-W, Kimmelstiel-Wilson; Ccr, creatinine clearance rate. To convert serum creatinine in μmol/L
to mg/dL, multiply by 0.0113; creatinine clearance rate in mL/s/1.73m2 to mL/min/1.73m2, multiply by 60.0. The listed P
values are based on ANOVA or Chi-square test. * P < 0.05 and ** P < 0.01versus lean group. ‡ P < 0.01 versus overweight
group.
21
Table 2. The profile of sub-cohort with a creatinine clearance (Ccr) of more than 90 mL/min/1.73
m2.
P
Total
Lean
sub-group
Overweight
sub-Group
Obese
sub-Group
129
46
51
32
Age (years)
52.6 ± 9.05
53.1 ± 9.36
52.1 ± 9.04
52.5 ± 8.82
0.883
Male sex (%)
78 (60.5%)
28 (60.9%)
31 (60.8%)
19 (59.3%)
0.987
BMI (kg/m2)
25.9 ± 3.05
23.0 ± 1.36
26.4 ± 0.84
30.5 ± 1.73
-
148 ± 38
138 ± 31
151 ± 40
159 ± 42**
0.027
93 (72.1%)
28 (60.9%)
37 (72.5%)
28 (87.5%)*
0.036
83.6 ± 68.8
91.7 ± 57.4
80.8 ± 63.8
76.6 ± 59.6
0.746
22.0 ± 25.6
20.0 ± 25.3
24.7 ± 26.1
20.5 ± 26.7
0.549
131 ± 48
134 ± 52
122 ± 35
143 ± 60
0.184
HbA1c (%)
6.81 ± 1.46
7.04 ± 1.71
6.48 ± 1.21
7.03 ± 1.35
0.133
Mean blood pressure (mm Hg)
105 ± 13.4
106 ± 15.3
103 ± 11.7
105 ± 12.9
0.364
Proteinuria (g/24h)
2.36 ± 2.33
2.39 ± 2.39
2.29 ± 2.32
2.43 ± 2.33
0.901
3.5g/24h (%)
30 (23.2%)
9 (19.6%)
13 (25.5%)
8 (25.0%)
0.760
Serum albumin (g/dL)
3.66 ± 0.77
3.47 ± 0.74
3.69 ± 0.77
3.78 ± 0.81
0.224
Serum creatinine (mg/dL)
0.88 ± 0.25
0.89 ± 0.21
0.89 ± 0.27
0.86 ± 0.24
0.987
12.7± 2.2
12.0 ± 2.0
12.8 ± 2.2
13.6 ± 2.2
0.016
Anemia (%)
33 (25.6%)
19 (41.3%)
10 (19.6%)
4 (12.5%)
0.007
High hemoglobin (%)
17 (13.2%)
5 (10.9%)
6 (11.8%)
6 (18.8%)
0.338
5.45 ± 0.0.55
4.79 ± 0.31
5.44±0.57*
6.40±0.71**
0.014
Meanglobal sclerosis (%)
16.3 ± 16.4
13.3 ± 13.6
15.7 ± 17.0
21.7 ± 19.6
0.178
Mesangial expansion (0-3)
1.70 ± 0.80
1.96 ± 0.84
1.54 ± 0.78
1.62 ± 0.59
0.698
K-W nodule (%)
55 (42.6%)
27 (58.7%) 18 (35.3%)*
10 (31.3%)*
0.012
Interstitial fibrosis (0-3)
1.20 ± 0.66
1.62 ± 0.64
1.50 ± 0.59
1.23 ± 0.31
0.430
Tubular atrophy (0-3)
0.98 ± 0.30
1.05 ± 0.32
0.95 ±0.30
0.94 ± 0.24
0.267
N. of patients
Ccr (mL/min/1.73m2)
>150 mL/min/1.73m2 (%)
Known duration of diabetes
(months)
Known duration of proteinuria
(months)
Fasting glucose (mg/dL)
Hemoglobin (g/dL)
Volume of glomerulus (×106 μm3)
value
NOTE. Values were expressed as mean ± SD or number (percentage); Abbreviation: BMI, body mass index; K-W,
Kimmelstiel-Wilson; Ccr, creatinine clearance rate. To convert serum creatinine in mol/L to mg/dL, multiply by 0.0113;
creatinine clearance rate in mL/s/1.73m2 to mL/min/1.73m2, multiply by 60.0. The listed P values are based on ANOVA
or Chi-square test. * P < 0.05 and ** P < 0.01 versus lean group.
22
Supplemental Table 1. Epidemiological characteristics of subjects with diabetic nephropathy.
All DN
Analyzed DN
757
264
BMI (kg/m2)
25.9 ± 3.05
25.5±3.39
0.454
Age (years)
52.6 ± 9.54
53.1 ± 9.06
0.622
No. of patients
Male sex (%)
466（61.5%） 154（58.3%）
P value
0.380
Known duration of diabetes (months)
107 ± 67.0
111 ± 73.7
0.249
Known duration of proteinuria
(months)
23.2 ± 35.6
27.7 ± 41.7
0.326
Fasting glucose (mg/ dL)
128± 45.2
124 ± 44.8
0.132
HbA1c (%)
6.80 ± 1.46
6.66 ± 1.33
0.272
Mean blood pressure (mmHg)
105 ± 13.4
108 ± 14.2
0.470
Proteinuria (g/24h)
2.96 ± 3.04
3.09 ± 2.32
0.569
Serum albumin (g/dL)
3.62 ± 0.77
3.45 ± 0.74
0.251
Serum creatinine (mg/dL)
2.13 ± 1.86
2.02 ±2.02
0.847
Ccr (mL/min/1.73m2)
94.3 ± 42.9
97.8 ± 53.4
0.219
Uric acid (μmol/L)
373 ± 94.0
400 ± 108
0.147
Hemoglobin (g/dL)
10.8 ± 2.2
11.2 ± 2.6
0.216
NOTE. Values were expressed as expressed as mean ± SD and categorical data expressed as number (%).Abbreviation:
BMI, body mass index. To convert serum creatinine in μmol/L to mg/dL, multiply by 0.0113; creatinine clearance rate in
mL/s/1.73m2 to mL/min/1.73m2, multiply by 60.0. The listed P values are based on student’s test or Chi-square test. * P <
0.05 and ** P < 0.01versus lean group. ‡ P < 0.01 versus overweight group.
23